harness

# Contenox **An agent harness for policy-bound, vendor-agnostic AI-assisted software engineering.** Contenox runs authored agent workflows as a local process. The policy that gates each tool call is a file the operator wrote, enforced by the harness before anything runs. Backends are configuration; sessions, approvals and per-step records stay on disk. The harness is the product. One binary serves the CLI and a local cockpit, editors attach over ACP, and the model named in a request is the model that serves it — or the run stops with the candidates it could have used. > **What Contenox is not:** it is not an autonomous coding employee, not a hosted > autopilot, and not a vendor's harness. It is a local runtime for AI-assisted > work that keeps the operator accountable for what runs. Docs: **[contenox.com](https://contenox.com)** --- ## For Work That Touches Real Systems Contenox is purpose-built for high-consequence engineering environments: production repositories, internal APIs, infrastructure scripts, operational dashboards, release pipelines, and systems of record. In these environments, an "AI agent" cannot mean "give a model broad credentials and hope for the best." It requires a strict runtime boundary: * **Explicit tools & policies** to govern actions. * **Local state** to preserve privacy. * **Human-in-the-loop (HITL) approval** for execution. * **Reviewable evidence** for auditing. The core issue is not that agents can act; it is agents acting outside a boundary the operator authors. The model can reason, inspect, and propose—but the **Chain** decides what it may touch, and the **operator** decides what it may change. --- ## Install ```bash curl -fsSL https://contenox.com/install.sh | sh ``` ### Inspect Before Installing If you prefer to audit the installation script first: ```bash curl -fsSLO https://contenox.com/install.sh less install.sh sh install.sh ``` *Pre-built release downloads and source builds are also available on the [releases page](https://github.com/contenox/harness/releases).* --- ## Quick Start <!-- TAG=v0.36.0 --> ```bash contenox setup # Choose a provider/model for this machine contenox "say hello world in python" # Query directly from the CLI contenox chat -e # Open $EDITOR to compose a rich prompt ``` Manage past contexts effortlessly using `contenox session list` and `contenox session switch <name>`. ### Smart Dual-Model Routing Inline autocomplete runs on a dedicated model separate from the main chat. This ensures editor ghost text stays entirely local and ultra-low latency, while complex chat queries can leverage larger frontier models: ```bash # Rich chat routed to a hosted model contenox config set default-provider openai contenox config set default-model gpt-5-mini # Ghost text routed to a small, fast model contenox config set default-autocomplete-provider ollama contenox config set default-autocomplete-model qwen2.5-coder:7b ``` --- ## Core Use Cases Contenox excels when workflows are specific, repeatable, and require explicit guardrails: * **Reviewing Diffs:** Run tests, summarize architectural risks, and gate destructive operations behind manual approvals. * **Drafting Release Evidence:** Automatically aggregate git logs, PRs, issue tickets, and CI outputs into clean changelogs, deployment checklists, and reviewer packets. * **Wrapping Internal APIs:** Safely expose subsets of OpenAPI specs while masking sensitive tenant/environment arguments and requiring authorization for mutating calls. * **Automating Repo Chores:** Ingest an issue tracking item, generate a patch, run local validation checks, and draft the PR description. * **Inspecting Live Operations:** Query diagnostic dashboards, shell scripts, or Model Context Protocol (MCP) tools via tightly scoped policies rather than broad, persistent credentials. * **Edge Autocomplete:** Offload editor suggestions to local workstation models while maintaining high-powered reasoning in chat. The exact same Chain runs seamlessly across the **Terminal, Zed, JetBrains, AionUi,** or any standard ACP client. --- ## Security & Runtime Protection | Identified Risk | Contenox Mitigation | | --- | --- | | **Fleeting Agent History** | Chains are declarative files: easily reviewable, version-controlled, and repeatable. | | **Unbounded Agent Access** | Enforced via strict tool allowlists, localized command policies, and tightly scoped API definitions. | | **Post-Damage Review** | Destructive actions are systematically blocked by human-in-the-loop approval gates prior to execution. | | **Leaky Internal APIs** | Curated OpenAPI subsets encapsulate hidden environment variables, auth tokens, and tenant arguments. | | **Vendor Lock-in** | Provider and model routing live in configuration files, entirely decoupled from application logic. | | **Frontier Model Budget Burn** | Routine tasks and linting checks are automatically routed to local or private-network infrastructure. | | **Exfiltration of Team Data** | All interactive sessions, states, configs, and runtime logs remain completely local. | --- ## Architectural Fit Contenox serves as the local agent runtime layer running between your interface and your infrastructure. | Ecosystem | The Contenox Paradigm | | --- | --- | | **IDE Copilots** | Editor assistance is only one piece of the puzzle. Workflows must execute uniformly across the terminal, IDEs, and independent headless scripts. | | **CLI Coding Agents** | A single coding loop is not a structured runtime. Contenox adds multi-session persistence, strict tool authorization, explicit model routing, and human gates. | | **LangChain / Frameworks** | Software development libraries are not end-user products. Contenox provides an out-of-the-box executable runtime tailored for engineers and teams. | | **Dify / n8n / Web Tools** | Workflows touching local source code and specialized internal infrastructure should never depend on a third-party SaaS control plane. | | **Ollama Wrappers** | A model provider is not a workflow boundary. Contenox introduces native Chains, secure tool definitions, and dynamic routing across hybrid infrastructure. | --- ## Connect Your Stack Any asset accessible via an OpenAPI spec, a shell command, or an MCP server can be transformed into a secure tool inside a Contenox Chain: ```bash # Connect any Model Context Protocol (MCP) server contenox mcp add notion https://mcp.notion.com/mcp --auth-type oauth # Wrap an internal HTTP API using its OpenAPI specification contenox tools add erp_billing \ --url https://erp.internal.example.com \ --spec ./billing-subset.yaml # Bind the local shell under a strictly defined Chain policy contenox --shell "check Proxmox and flag anything red" ``` --- ## Editor Integration Contenox natively communicates via the [Agent Client Protocol (ACP)](https://github.com/zed-industries/agent-client-protocol) over standard I/O. ### Zed Integration Add the following snippet to your `~/.config/zed/settings.json`: ```json { "agent_servers": { "Contenox": { "type": "custom", "command": "contenox", "args": ["acp"] } } } ``` Tool invocations render dynamically as interactive UI cards showing the underlying paths, human-in-the-loop prompts hook directly into the editor's native permissions, and full session history replays automatically upon reopening projects. ### Other Environments * **Web Interface:** Running `contenox serve` mounts your active sessions, chains, and backends locally inside **Beam**, the bundled web UI. *Step-by-step guides:* [Zed](https://contenox.com/docs/integrations/editors/zed/) | [JetBrains](https://contenox.com/docs/integrations/editors/jetbrains/) | [AionUi](https://contenox.com/docs/integrations/editors/aionui/). --- ## Managing Backends Routing rules are treated as system configuration, not application logic. Add hosted, local, or private network backends seamlessly: ```bash # Private infrastructure & local inference contenox backend add ollama --type ollama contenox backend add myvllm --type vllm --url http://gpu-host:8000 # Commercial cloud providers contenox backend add openai --type openai --api-key-env OPENAI_API_KEY contenox backend add anthropic --type anthropic --api-key-env ANTHROPIC_API_KEY contenox backend add gemini --type gemini --api-key-env GEMINI_API_KEY # Set global operational routing defaults contenox config set default-model qwen2.5:7b contenox config set default-provider ollama ``` --- ## Building From Source ### Prerequisites * **Go 1.25+** ```bash # Clone the repository git clone https://github.com/contenox/harness cd runtime # Build the main core CLI make build-contenox ``` --- ## Core Dependencies The `contenox` core CLI is written entirely in pure Go. Go dependencies are maintained standardly in `go.mod`. --- Questions? Reach out at **hello@contenox.com**